Experienced the same issue. It seem the problem is that by default, chromosome names are not in the form "chr1" etc., but just "1" etc. The solution is to use function snpgdsOption() to redefine your chromosome names to whatever form they are in your vcf file : snpgdsVCF2GDS(vcf, "ccm.gds", method="copy.num.of.ref", option=snpgdsOption(chr1=1, chr2=2, chr3=3, chr4=4, chr5=5, chr6=6, chr7=7, chr8=8, chr9=9, chr10=10, chr11=11, chr12=12, chr13=13, chr14=14, chr15=15, chr16=16, chr17=17, chr18=18, chr19=19, chr20=20, chr21=21, chr22=22, chrX=23, chrY=24, chrM=25))

Another solution is to add autosome.only=FALSE in snpgdsPCA() - it then takes all your chromosomes whatever their names are.

ccm_pca$eigenvect[,1],ccm_pca$eigenvect[,2] implies that you are plotting between eigen vectors 1 and eigen vectors 2 ... PC1 and PC2...

Have you find how to manage it ?

Hi, I found this thread really helpful . My data is grouped in 4 different populations and I managed to get them labelled as such by doing something similar to the following. Following on from Zev's code above....

>genofile <- snpgdsOpen("ccm.gds")
>sample.id <- read.gdsn(index.gdsn(genofile, "sample.id"))
>sample.id
[1] "Sample1"   
[2] "Sanple2"  
[3] "Sample3"  
[4] "Sample4" 
[5] "Sample5"

In a text file, list the group name of each sample in sample.id, one group per line with each line corresponding to the group of the corresponding sample. For example if Sample 1 and 2 in sample.id were in 'Group 1' and Sample 3 - 5 were in 'Group 2', you'd have:

Group1
Group1
Group2
Group2
Group2

Save the file as 'pops.txt' and then:

>pop_code <- scan("pops.txt", what=character())
>cbind( sample.id, pop_code)

>ccm_pca<-snpgdsPCA(genofile, autosome.only=FALSE, num.thread=4)

>tab <- data.framesample.id = ccm_pca$sample.id,
              pop = factor(pop_code)[match(ccm_pca$sample.id, sample.id)],
              EV1 = ccm_pca$eigenvect[,1],    # the first eigenvector
              EV2 = ccm_pca$eigenvect[,2],    # the second eigenvector
              stringsAsFactors = FALSE)

>plot(tab$EV2, tab$EV1, col=as.integer(tab$pop), xlab="eigenvector 2", ylab="eigenvector 1")
legend("bottomright", legend=levels(tab$pop), pch="o", col=1:nlevels(tab$pop))

And that should do it!

The original question was posted almost 8 years ago. You may consider creating a new question relating to your specific issue. Also, if you choose to do this, then provide a lot more details and show the code that you have already used.

Note that there are many other questions already online (on other forums) where it is explained how to colour vectors differently in a plot.

I was wondering if you were able to find any assistance regarding this? I am not easily able to change the color vectors on my plot! Thank you!

Update: I believe I found a specific solution for the code posted above and will share here after testing out.

Update: To change the color palette after plotting you can define a color vectors as such:

jColors <- c('chartreuse3', 'cornflowerblue', 'darkgoldenrod1', 'peachpuff3',
         'mediumorchid2', 'turquoise3', 'wheat4', 'slategray2') ## choosing specific colors for your plot!

Then include your color palette in your plot. I assigned colors based on the 8 populations in my PCA.

plot(tab_popr$EV2, tab_popr$EV1, col=jColors[as.integer(tab_popr$pop)], xlab = "EV2", ylab = "EV1")
legend("topleft", legend = levels(tab_popr$pop), pch = "o", col = jColors[1:nlevels(tab_popr$pop)])

What is the error message? Can you post part of the VCF?

SNPRelate has been removed from CRAN. You need to install it from Bioconductor now.

How would you plot the resulting output?